Based on prior knowledge, I will analyze the relationship between the Age feature and the likelihood of a person having diabetes. To do this, I will use typical ranges of values for age and compare the distribution of ages among individuals with and without diabetes.

```json
{
	"yes": [40.0, 45.0, 50.0, 55.0, 60.0],
	"no": [25.0, 30.0, 35.0, 38.0, 42.0]
}
```

In the target class "yes" (people with diabetes), typical ages could be around 40, 45, 50, 55, and 60 years. Whereas in the target class "no" (people without diabetes), typical ages could be around 25, 30, 35, 38, and 42 years. These values are based on general knowledge and might vary depending on the specific dataset being analyzed.